"""
演示数据集的测试等
"""
import UCFRS


# 演示数据集：一个“用户-电影评分”小型测试数据，包括 7 位用户和 6 部电影
prefs = {
    'Lisa Rose':
        {'Lady in the Water': 2.5, 'Snakes on a Plane': 3.5,
         'Just My Luck': 3.0, 'Superman Returns': 3.5, 'You, Me and Dupree': 2.5,
         'The Night Listener': 3.0},
    'Gene Seymour':
        {'Lady in the Water': 3.0, 'Snakes on a Plane': 3.5,
         'Just My Luck': 1.5, 'Superman Returns': 5.0, 'The Night Listener': 3.0,
         'You, Me and Dupree': 3.5},
    'Michael Phillips':
        {'Lady in the Water': 2.5, 'Snakes on a Plane': 3.0,
         'Superman Returns': 3.5, 'The Night Listener': 4.0},
    'Claudia Puig':
        {'Snakes on a Plane': 3.5, 'Just My Luck': 3.0,
         'The Night Listener': 4.5, 'Superman Returns': 4.0,
         'You, Me and Dupree': 2.5},
    'Mick LaSalle':
        {'Lady in the Water': 3.0, 'Snakes on a Plane': 4.0,
         'Just My Luck': 2.0, 'Superman Returns': 3.0, 'The Night Listener': 3.0,
         'You, Me and Dupree': 2.0},
    'Jack Matthews':
        {'Lady in the Water': 3.0, 'Snakes on a Plane': 4.0,
         'The Night Listener': 3.0, 'Superman Returns': 5.0, 'You, Me and Dupree': 3.5},
    'Toby':
        {'Snakes on a Plane': 4.5, 'You, Me and Dupree': 1.0, 'Superman Returns': 4.0}
}

if __name__ == '__main__':
    p1 = 'Lisa Rose'
    p2 = 'Gene Seymour'
    print(UCFRS.sim_distance(prefs, p1, p2))
    print(UCFRS.sim_pearson(prefs, p1, p2))
    print(UCFRS.sim_cosine(prefs, p1, p2))
